Structured light depth extraction refers to a method for measuring depth that includes projecting patterns onto an object, detecting reflected patterns from the object, and using pixel displacements in the transmitted and reflected patterns to calculate the depth or distance from the object from which the light was reflected. Conventionally, structured light depth extraction has been performed using a slide projector. For example, a series of patterns on individual slides may be projected onto an object. A detector, such as a camera, detects reflected patterns. The pixels in the projected patterns are mapped manually to the pixels in the reflected patterns. Given the position of the projector and the camera and the pixel offsets, the location of the object can be determined.
In real-time structured light depth extraction systems, images are required to be rapidly projected onto an object and detected synchronously with the projection. In addition, the calculations to determine the depth of the object are required to be extremely fast. Currently, in real-time structured light depth extraction systems, an incandescent lamp and a collimator are used to generate a collimated beam of light. In one exemplary implementation, the collimated beam of light is projected onto a pattern generator. The pattern generator reflects the transmitted light onto the object of interest. The reflected pattern is detected by a camera that serves a dual purpose of detecting structured light patterns and reflected broadband light. A specialized image processor receives the reflected images and calculates depth information.
While this conventional structured light depth extraction system may be effective in some situations, incandescent light has poor photonic efficiency when passed through the optics required to image surfaces inside a patient in an endoscopic surgical environment. One reason that incandescent light has been conventionally used for real-time structured light depth extraction systems is that an incandescent lamp was the only type of light source thought to have sufficient power and frequency bandwidth to illuminate objects inside of a patient. Another problem with this conventional structured light depth extraction system is that using a single camera for both broadband light detection and depth extraction is suboptimal since the pixel requirements for broadband light detection are greater than those required for depth extraction, and the required frame speed is greater for depth extraction than for broadband light detection. Using a single camera results in unnecessary data being acquired for both operations. For example, if a high-resolution, high-speed camera is used for depth extraction and broadband light detection, an unnecessary number of images will be acquired per unit time for broadband light detection and the resolution of the images will be higher than necessary for depth extraction. The additional data acquired when using a single camera for both broadband light detection and depth extraction increases downstream memory storage and processing speed requirements.
Accordingly, in light of these difficulties associated with conventional real-time structured light depth extraction systems, there exists a long-felt need for improved methods and systems for real-time structured light depth extraction for an endoscopic surgical environment.